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A Novel Bangla Spoken Numerals Recognition System Using Convolutional Neural Network

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Machine Intelligence and Emerging Technologies (MIET 2022)

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Abstract

Automatic speech recognition (ASR) converts human speech into text or words that can be understood and classified easily. Only digits from (0-9) were used in the few studies on Bangla number recognition systems, which completely ignored duo-syllabic and tri-syllabic numbers. Audio samples of (0-99) Bangla spoken numbers from Bangladeshi citizens of various genders, ages, and languages were used to construct a speech dataset of spoken numbers in this work. Time shift, speed tuning, background noise mixing, and volume tuning are among the audio augmentation techniques used on the raw speech data. Then, to extract meaningful features from the data, Mel Frequency Cepstrum Coefficients (MFCCs) are used. This research developed a Bangla number recognition system based on Convolutional Neural Networks (CNNs). Our proposed dataset includes the diversity of speakers in terms of age, gender, dialects and other criteria. The proposed method recognizes (0-99) Bangla spoken numbers with 89.61% accuracy across the entire dataset. The model’s efficacy was also evaluated using a 10-fold cross-validation procedure, with 89.74% accuracy for recognizing (0-99) Bangla spoken numbers across the entire dataset. This proposed method is also compared to some existing works in the field of recognizing spoken digits classes, demonstrating its dominance.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Khulna University of Engineering and Technology, Khulna, 9203, Bangladesh

    Ovishake Sen, Pias Roy &  Al-Mahmud

Authors
  1. Ovishake Sen
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  2. Pias Roy
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  3. Al-Mahmud
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Corresponding author

Correspondence to Ovishake Sen .

Editor information

Editors and Affiliations

  1. Noakhali Science and Technology University, Noakhali, Bangladesh

    Md. Shahriare Satu

  2. The University of Queensland, St. Lucia, QLD, Australia

    Mohammad Ali Moni

  3. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  4. Daffodil International University, Dhaka, Bangladesh

    Mohammad Shamsul Arefin

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Sen, O., Roy, P., Al-Mahmud (2023). A Novel Bangla Spoken Numerals Recognition System Using Convolutional Neural Network. In: Satu, M.S., Moni, M.A., Kaiser, M.S., Arefin, M.S. (eds) Machine Intelligence and Emerging Technologies. MIET 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 490. Springer, Cham. https://doi.org/10.1007/978-3-031-34619-4_28

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  • DOI: https://doi.org/10.1007/978-3-031-34619-4_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34618-7

  • Online ISBN: 978-3-031-34619-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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